Bulgarian Journal of Agricultural Science, 12 (2006), National Centre for Agrarian Sciences

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1 405 Bulgarian Journal of Agricultural Science, 12 (2006), National Centre for Agrarian Sciences Analysis of the Influence of Gene Environment Interaction on the Phenotypic Values of Correlation and Regression Indexes in Crosses between Seed and Seedless Varieties of Vine (V. vitifera L.) V. ROYTCHEV Agricultural University, BG Plovdiv, Bulgaria Abstract ROYTCHEV, V., Analysis of the influence of gene environment interaction on the phenotypic values of correlation and regression indexes in crosses between seed and seedless varieties of vine (V. vitifera L.). Bulg. J. Agric. Sci., 12: We have studied the influence of the gene-environment interaction on the phenotypic values of the correlation and regression indexes in crosses between seed and seedless varieties of vine. It was established that in the F1 generation of almost all crosses the phenotypic correlation indexes are multidirectional but well pronounced. As concerns the correlation indexes, the genotype-environment effects in the different offspring are relatively weaker in crosses like Super Early Bolgar x Russalka 1 and Armira x Russalka 1 and stronger in Hybrid x Russalka. The phenotypic regression indexes also vary within a broad range and their genotype-environment effect is best pronounced in crosses Super Early Bolgar x Russalka 1 and Armira x Russalka 1, and less in Hybrid x Russalka. The analysis offers the opportunity to use these correlation and regression indexes to forecast the selection of elite hybrids according to one of the correlating traits. Key words: genotype-environment, phenotypic values, correlation and regression indexes, sugars and acids, crosses between seed and seedless sorts of vine Introduction The variability of the phenotypic values of quantitative traits in separate genotypes tested in different conditions is due to the additive effect of the environment and the genes that interact with it. The effect of the additive genes on the variability is the same for all genotypes subject to research while the genes that interact with the environment determine the differences for each separate genotype (Fedin et al., 1980; Mather and Jinks, 1971). Similar are the factors that determine the phenotypic values of the correlation and regression indexes by environment. Their variability depends on genetic and environmental factors, including non additive effects, which can not be immediately derived. From the point of view of

2 406 V. Roytchev selection it is important to decompose the phenotypic correlation and regression indexes into genotype and paratype ones. Depending on the purposes of the experiment, there are various statistical methods based on dispersion and co-variation analyses (Rokitsky, 1978; Genchev et al., 1975; Lakin, 1990) as well as the mathematical model of Perkins and Jinks (1968, 1968). Being a vegetative plant, vine is a particularly good subject for this kind of research because the analysis of hybrids allows individual reading of the quantitative traits by year (Bozhinova-Boneva, 1982; Pospisilova and Korpas, 1998). The analysis of the effect of genes, which interact with the environment, will make it possible to select precious from the point of view of ampelography and economy elite forms. This research is especially important in heterozygote populations of offspring in F 1 generation. The purpose of this study is to characterize the F1 generation obtained from crossing seed and seedless varieties of vine with regard to the effect of gene-environment interaction on the variation of correlation and regression indexes by individual plants. Materials and Methods The experimental work includes offspring of F 1 generation of the crosses Super Early Bolgar x Russalka 1, Armira x Russalka 1 and Hybrid x Russalka. The analysis of hybrids was conducted at the selection field of the Viticulture Department of the Agricultural University - Plovdiv. In 20 plants of each cross were individually read the quantity of sugars and acids in the grape over the period The quantity of sugars (s, %) was measured at the stage of technological (ready to eat) maturity using an ABBE laboratory refractometer, and the total quantity of acids (a, g/dm 3 ) - by titration with 0.1 n NaOH (Bulgarian Ampelography, 1990). The phenotypic correlation and regression indexes ( r кз, bкз) are calculated individually for each plant and the genotype ones - by the mean values of these traits in all plants by environment (year) r, b ( к з к з ), which do not reflect the effect of gene-environment interaction and can be used as standard (St) (Snedecor, 1957; Rokitsky, 1967; Lidanski, 1988). The effect of the gene-environment interaction on the variation of phenotypic, correlation and regression indexes is expressed by the differences ( d1 = r k 3 r and d k3 2 = b k 3 b ), k 3 and their reliability - by the method of small extracts (Rokitsky, 1967). As base for comparison of these effects in the separate genotypes were used the indexes ( кз ) 1 ( кз ) k = r / r 1and k = b / b 1 k з When d=0 or when it is within the range tоn < P 5%, it can be considered that the effects of the parameter gd on r кз and b кз are small and can not be proved, and if t оn < P 5% they are well pronounced. The indexes k and k 1 reflect the grade of this effect with consideration to the correlation and regression indexes. The bigger the amplitude difference к=+0, the more important are the genotype-environment effects and vice-versa, which also allows them to be arranged. These indexes can be applied not only on tested genotypes in an extract but also to the results of similar k з

3 Analysis of the Influence of Gene Environment Interaction on the Phenotypic analyses because parameters are used as St. r кз and b Results and Discussion The results of the analysis by cross arranged by values of the index k are given in Tables 1-3. The results for the cross Super Early Bolgar x Russalka show that the phenotypic correlation indexes (r кз ) кз vary within a broad range (Table 1). The values for offspring 1-6 are positive and the others are negative. Among them this parameter is proved in 1, 17, 18, 19 and 20. The genotype correlation r кз = is proved at the 3rd degree. The effects of the gene-environment interaction (d 1 ) are the most pronounced in offspring 1-4 proved at 1st-3rd degree and in the others the criterion td 1 is in the range Table 1 Effect of the interaction between genotype and environment on the correlation and regression coefficients of the traits sugar and acid content in generation F 1 of the hybrid combination Super Early Bolgar x Rusalka 1 P r кз d 1 td 1 k b кз d 2 td 2 k St df = 4; P 5% = 2.78; P 1% = 4.60; P 0.1% = 8.61

4 408 V. Roytchev at Р 5% = Particularly characteristic in this regard is the index k in which the offspring are arranged by level of manifestation of the genotype-environment effect. Close to the standard and with relatively high phenotypic values are the offspring 13-20, which should be taken into consideration in selection. The value of the phenotypic regression index (b кз ) is positive for the 1st through 6th offspring and negative in the others. The genotype-environment effect in regression indexes (d 2 ), expressed by the reliability of the parameter td2, are the most manifested in offspring 1-7, 11, 12, 14, 15, 17 and 20 where tоn P 5%. Ranged by the values of index k 1 closest to St are offspring 10, 14, 16, 18 and 20, which could be successfully used for the purposes of selection. The data for the cross Armira x Table 2 Effect of the interaction between genotype and environment on the correlation and regression coefficients of the traits sugar and acid content in generation F 1 of the hybrid combination Super Early Bolgar x Rusalka 1 P r кз d 1 td 1 k b кз d 2 td 2 k St df = 4; P 5% = 2.78; P 1% = 4.60; P 0.1% = 8.61

5 Analysis of the Influence of Gene Environment Interaction on the Phenotypic Russalka 1 show that the values of the phenotypic correlation indexes are high and proved at the 3 rd and 2 nd degree in offspring 1, (Table 2). The genotype correlation index (St) is also high, with negative value when proved at the 2 nd degree. The genotype-environment effects expressed by parameter d 1 are proved at the 2 nd -3 rd degree and found only in offspring 1-3. They are remarkably low in offspring with values for td 2 = 0.00 to 0.57 и к = 0.00 to The phenotypic regression indexes also vary within a wide range with positive values in P (1-4) and negative in the others. The genotype regression index (St) is relatively high with negative value. In most cases the effect of the genes that interact Table 3 Effect of the interaction between genotype and environment on the correlation and regression coefficients of the traits sugar and acid content in generation F 1 of the hybrid comlination Hybrid x Russalka P r кз d 1 td 1 k b кз d 2 td 2 k St df = 4; P 5% = 2.78; P 1% = 4.60; P 0.1% = 8.61

6 410 with the environment is well visible and proved at 1 st -3 rd degree. This parameter is not proved in offspring 1, 6, 8, 12, 13, 16, 17, 18 and 20, which with consideration to к 1 are arranged as follows: 17, 16, 18, 13, 20, 12, 8, 6, and 1. The value of к 1 is negative, which means that in all offspring the genes that interact with the environment decrease the phenotypic values of the regression indexes. The phenotypic correlation indexes for the cross Hybrid x Russalka vary between plants and they are only reliable in 1-3 (Table 3). The values are positive in offspring and negative in the others. The value of the genotype correlation index (St) is high and positive. The genotype-environment effects are the best visible in offspring 1-9 and parameter d 1 is proved from 1 st to 3 rd degree. It is interesting to note that in almost all offspring the value of the index к is negative, which means that this effect decreases the phenotypic values of the correlation indexes. Similar is the variation in phenotypic regression indexes. The differences between b кз and b st are proved only in offspring 1 and 3. In the others, these effects are relatively better manifested in offspring 2, 5, 6, 7-16, where the values of td 2 are close to P5%. From the data about the index к 1 obtained it can be seen that offspring 20, 17, 18 and 19 present the less pronounced of genes that interact with the environment because their values are closer to the standard (к st = 0). The negative values of the studied feature also mean that these genes decrease the values of the phenotypic regression indexes. Conclusions In almost all crosses the phenotypic correlation indexes in many offspring are well manifested and some of them are highly proved. Their values are positive and negative and the correlative dependencies are not unidirectional. Very favorable to selection are the genotype correlation indexes, which have high values regardless of the sign. The genotype-environment effects in different offspring as concerns correlation indexes are relatively less pronounced in the crosses Super Early Bolgar x Russalka 1 and Armira x Russalka 1 and more pronounced in Hybrid x Russalka. Arranging the offspring in the different hybrid combinations allows their more efficient use for the purposes of selection. The phenotypic regression indexes, which are often used in selection, also vary within wide limits with positive and negative sign. The genotype-environment effects are the best manifested in the crosses Super Early Bolgar x Russalka 1 and Armira x Russalka 1 and less in Hybrid x Russalka. This analysis makes possible the use of correlation and regression indexes for forecasting the selection of elite hybrids by one of the correlating traits. References V. Roytchev Bozhinova-Boneva, I., Selection and genetic research aiming to improve the range of vine in the viniculture region of southern Bulgaria, Habilitation work, Applied Research viticulture and horticulture center "Acad. Nedelcho Nedelchev, town of Septemvri, 332 pp. (Bg).

7 Analysis of the Influence of Gene Environment Interaction on the Phenotypic Bulgarian Ampelography, General Ampelography. Publ. BAS, Sofia, Vol. 1, 296 pp. (Bg). Fedin, М. А., D. Ya. Silis and A. V. Smiryaev, Statistical Methods Of Genetic Analysis. Moscow, "Kolos", 207 pp. (Ru). Genchev, G., E.Marinkov, V.Iovcheva and A. Ognjanova, Biometrical Methods in Plant Growing, Genetics and Breeding. Sofia, Zemizdat, 322 pp. (Bg). Lakin, G. F., Biometry. Moscow, Visshaya shkola, 352 pp. (Ru). Lidanski, T., Statistical Methods in Biology and Agriculture. Zemizdat, Sofia, 374 pp. (Bg). Mather, K. and J. L. Jinks, Biometrical Genetics: The study of continuous variations. - New Jork: Cornell University Press, 382 pp. Rokitsky, P. F., Biological Statistics. Minsk, Vysheishaya shkola, 326 pp. (Ru). Rokitsky, P. F., Introduction to Statistical Genetics. 2nd edition, Minsk, Vysheishaya shkola, p. 448 (Ru). Perkins, J. M. and J. L. Jinks, Environmental and genotype - environmental components of variability. III. Multiple lines and crosses. Heredity, 23: Perkins, J. M. and J. L. Jinks, Environmental and genotype - environmental components of variability IV. Non-linear interactions for multiple inbred lines. Heredity, 23: Pospisilova, D. and O. Korpas, Nove Slachtenie vinica na Slovensku. Bratislava, 222 pp. Snedecor, G. W., Statistical metods applied to experiments in agriculture and biology. The Iowa State College Press. Ames Iowa, 534 pp. Received December, 12, 2005; accepted April, 3, 2006.